Convolutional Neural Networks as a Tool for Raman Spectral Mineral Classification Under Low Signal, Dusty Mars Conditions-Reference-Cited by-同舟云学术

Convolutional Neural Networks as a Tool for Raman Spectral Mineral Classification Under Low Signal, Dusty Mars Conditions

Published:2022-10 Issue:10 Volume:9 Page:
ISSN:2333-5084
Container-title:Earth and Space Science
language:en
Short-container-title:Earth and Space Science

Author:

Berlanga Genesis¹²^ORCID,Williams Quentin¹^ORCID,Temiquel Nathan³^ORCID

Affiliation:

1. Department of Earth and Planetary Sciences University of California—Santa Cruz Santa Cruz CA USA

2. BMSIS at NASA Ames Research Center Mountain View CA USA

3. Coursera Mountain View CA USA

Funder

National Science Foundation

Publisher

American Geophysical Union (AGU)

Subject

General Earth and Planetary Sciences,Environmental Science (miscellaneous)

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2021EA002125

Reference96 articles.

1. Abadi M. Agarwal A. Paul B. Brevdo E. Chen Z. Craig C. et al. (2016).TensorFlow: Large‐scale machine learning on heterogeneous distributed systems.

2. Temperature Dependence of the Homogeneous Broadening of Resonant Raman Peaks Measured by Single-Molecule Surface-Enhanced Raman Spectroscopy

3. Baseline correction using asymmetrically reweighted penalized least squares smoothing

4. Remote Raman spectroscopy of natural rocks

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Dataset formation for sem-based images of commercial minerals using ml algorithms: case study for zircon in the Egyptian mountains;Multimedia Tools and Applications;2024-08-16

2. RamanFormer: A Transformer-Based Quantification Approach for Raman Mixture Components;ACS Omega;2024-05-23

3. A New Semi-supervised Tool-wear Monitoring Method using Unreliable Pseudo-Labels;Measurement;2024-02

4. Two-stage deep learning pipeline for automated mineral classification in planetary Raman spectra;CLEO 2024;2024

5. Using artificial intelligence to transform astrobiology;Nature Astronomy;2023-12-28